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<div class="header">
  <div class="summary">
<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-static-methods">Static Public Member Functions</a> &#124;
<a href="#pro-methods">Protected Member Functions</a> &#124;
<a href="#pro-attribs">Protected Attributes</a> &#124;
<a href="classactionNet-members.html">List of all members</a>  </div>
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<div class="title">actionNet Class Reference<div class="ingroups"><a class="el" href="group__deepVision.html">DNN Vision Library (jetson-inference)</a> &raquo; <a class="el" href="group__actionNet.html">actionNet</a></div></div>  </div>
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<p>Action/activity classification on a sequence of images or video, using TensorRT.  
 <a href="classactionNet.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="actionNet_8h_source.html">actionNet.h</a>&gt;</code></p>
<div class="dynheader">
Inheritance diagram for actionNet:</div>
<div class="dyncontent">
 <div class="center">
  <img src="classactionNet.png" usemap="#actionNet_map" alt=""/>
  <map id="actionNet_map" name="actionNet_map">
<area href="classtensorNet.html" title="Abstract class for loading a tensor network with TensorRT." alt="tensorNet" shape="rect" coords="0,0,66,24"/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a90871793d4922b61bc7ac81d7355d685"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a90871793d4922b61bc7ac81d7355d685">~actionNet</a> ()</td></tr>
<tr class="memdesc:a90871793d4922b61bc7ac81d7355d685"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destroy.  <a href="classactionNet.html#a90871793d4922b61bc7ac81d7355d685">More...</a><br /></td></tr>
<tr class="separator:a90871793d4922b61bc7ac81d7355d685"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4338f944254f92fe33572ea1cc7a9736"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a4338f944254f92fe33572ea1cc7a9736"><td class="memTemplItemLeft" align="right" valign="top">int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classactionNet.html#a4338f944254f92fe33572ea1cc7a9736">Classify</a> (T *image, uint32_t width, uint32_t height, float *confidence=NULL)</td></tr>
<tr class="memdesc:a4338f944254f92fe33572ea1cc7a9736"><td class="mdescLeft">&#160;</td><td class="mdescRight">Append an image to the sequence and classify the action, returning the index of the top class.  <a href="classactionNet.html#a4338f944254f92fe33572ea1cc7a9736">More...</a><br /></td></tr>
<tr class="separator:a4338f944254f92fe33572ea1cc7a9736"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4c7b95bad0cfa696339590020bc4d7c9"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a4c7b95bad0cfa696339590020bc4d7c9">Classify</a> (void *image, uint32_t width, uint32_t height, <a class="el" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format, float *confidence=NULL)</td></tr>
<tr class="memdesc:a4c7b95bad0cfa696339590020bc4d7c9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Append an image to the sequence and classify the action, returning the index of the top class.  <a href="classactionNet.html#a4c7b95bad0cfa696339590020bc4d7c9">More...</a><br /></td></tr>
<tr class="separator:a4c7b95bad0cfa696339590020bc4d7c9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afde433b5b807ef910787f1d999cef79a"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#afde433b5b807ef910787f1d999cef79a">GetNumClasses</a> () const</td></tr>
<tr class="memdesc:afde433b5b807ef910787f1d999cef79a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of image recognition classes.  <a href="classactionNet.html#afde433b5b807ef910787f1d999cef79a">More...</a><br /></td></tr>
<tr class="separator:afde433b5b807ef910787f1d999cef79a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abe3946ca2ec6528cde8af9dd90d986ff"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#abe3946ca2ec6528cde8af9dd90d986ff">GetClassLabel</a> (int index) const</td></tr>
<tr class="memdesc:abe3946ca2ec6528cde8af9dd90d986ff"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the description of a particular class.  <a href="classactionNet.html#abe3946ca2ec6528cde8af9dd90d986ff">More...</a><br /></td></tr>
<tr class="separator:abe3946ca2ec6528cde8af9dd90d986ff"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adcfadd35f1c5bf00e4556d4bb15b7ae4"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">GetClassDesc</a> (int index) const</td></tr>
<tr class="memdesc:adcfadd35f1c5bf00e4556d4bb15b7ae4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the description of a particular class.  <a href="classactionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">More...</a><br /></td></tr>
<tr class="separator:adcfadd35f1c5bf00e4556d4bb15b7ae4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab1fa2e71897572a2e894cace9078ec36"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#ab1fa2e71897572a2e894cace9078ec36">GetClassPath</a> () const</td></tr>
<tr class="memdesc:ab1fa2e71897572a2e894cace9078ec36"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the file containing the class descriptions.  <a href="classactionNet.html#ab1fa2e71897572a2e894cace9078ec36">More...</a><br /></td></tr>
<tr class="separator:ab1fa2e71897572a2e894cace9078ec36"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8ba975e3e175e751c10e2121d339a4d0"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a8ba975e3e175e751c10e2121d339a4d0">GetThreshold</a> () const</td></tr>
<tr class="memdesc:a8ba975e3e175e751c10e2121d339a4d0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the confidence threshold used for classification.  <a href="classactionNet.html#a8ba975e3e175e751c10e2121d339a4d0">More...</a><br /></td></tr>
<tr class="separator:a8ba975e3e175e751c10e2121d339a4d0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9628498f941ed6709c6b2e13bbb79e29"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a9628498f941ed6709c6b2e13bbb79e29">SetThreshold</a> (float threshold)</td></tr>
<tr class="memdesc:a9628498f941ed6709c6b2e13bbb79e29"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the confidence threshold used for classification.  <a href="classactionNet.html#a9628498f941ed6709c6b2e13bbb79e29">More...</a><br /></td></tr>
<tr class="separator:a9628498f941ed6709c6b2e13bbb79e29"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6516543d67148a4a31efd156579676d4"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a6516543d67148a4a31efd156579676d4">GetSkipFrames</a> () const</td></tr>
<tr class="memdesc:a6516543d67148a4a31efd156579676d4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the number of frames that are skipped in between classifications.  <a href="classactionNet.html#a6516543d67148a4a31efd156579676d4">More...</a><br /></td></tr>
<tr class="separator:a6516543d67148a4a31efd156579676d4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0d1b5c7a23698972dc4d1646e2a23d49"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49">SetSkipFrames</a> (uint32_t frames)</td></tr>
<tr class="memdesc:a0d1b5c7a23698972dc4d1646e2a23d49"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the number of frames that are skipped in between classifications.  <a href="classactionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49">More...</a><br /></td></tr>
<tr class="separator:a0d1b5c7a23698972dc4d1646e2a23d49"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">~tensorNet</a> ()</td></tr>
<tr class="memdesc:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destory.  <a href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">More...</a><br /></td></tr>
<tr class="separator:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean=NULL, const char *input_blob=&quot;data&quot;, const char *output_blob=&quot;prob&quot;, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">More...</a><br /></td></tr>
<tr class="separator:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple output layers.  <a href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">More...</a><br /></td></tr>
<tr class="separator:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a68a6f21680ae91bc51bea376221d1c48 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a68a6f21680ae91bc51bea376221d1c48">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a68a6f21680ae91bc51bea376221d1c48 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple input layers.  <a href="classtensorNet.html#a68a6f21680ae91bc51bea376221d1c48">More...</a><br /></td></tr>
<tr class="separator:a68a6f21680ae91bc51bea376221d1c48 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;input_dims, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance (this variant is used for UFF models)  <a href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">More...</a><br /></td></tr>
<tr class="separator:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8f34a6001c2da01662b85670de9246e4 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a8f34a6001c2da01662b85670de9246e4">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &gt; &amp;input_dims, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a8f34a6001c2da01662b85670de9246e4 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple input layers (used for UFF models)  <a href="classtensorNet.html#a8f34a6001c2da01662b85670de9246e4">More...</a><br /></td></tr>
<tr class="separator:a8f34a6001c2da01662b85670de9246e4 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acb8076f6ab8d13b6507140826cf438d8 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#acb8076f6ab8d13b6507140826cf438d8">LoadEngine</a> (const char *engine_filename, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; std::string &gt; &amp;output_blobs, nvinfer1::IPluginFactory *pluginFactory=NULL, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:acb8076f6ab8d13b6507140826cf438d8 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a network instance from a serialized engine plan file.  <a href="classtensorNet.html#acb8076f6ab8d13b6507140826cf438d8">More...</a><br /></td></tr>
<tr class="separator:acb8076f6ab8d13b6507140826cf438d8 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaa4efe2b8d91fe914a22c87b725ac063 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aaa4efe2b8d91fe914a22c87b725ac063">LoadEngine</a> (char *engine_stream, size_t engine_size, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; std::string &gt; &amp;output_blobs, nvinfer1::IPluginFactory *pluginFactory=NULL, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:aaa4efe2b8d91fe914a22c87b725ac063 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a network instance from a serialized engine plan file.  <a href="classtensorNet.html#aaa4efe2b8d91fe914a22c87b725ac063">More...</a><br /></td></tr>
<tr class="separator:aaa4efe2b8d91fe914a22c87b725ac063 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2d6fe13696a49d61e9abfa9729153e65 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2d6fe13696a49d61e9abfa9729153e65">LoadEngine</a> (nvinfer1::ICudaEngine *engine, const std::vector&lt; std::string &gt; &amp;input_blobs, const std::vector&lt; std::string &gt; &amp;output_blobs, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a2d6fe13696a49d61e9abfa9729153e65 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load network resources from an existing TensorRT engine instance.  <a href="classtensorNet.html#a2d6fe13696a49d61e9abfa9729153e65">More...</a><br /></td></tr>
<tr class="separator:a2d6fe13696a49d61e9abfa9729153e65 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a89755f8e4b72ead7460deed394967386 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a89755f8e4b72ead7460deed394967386">LoadEngine</a> (const char *filename, char **stream, size_t *size)</td></tr>
<tr class="memdesc:a89755f8e4b72ead7460deed394967386 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a serialized engine plan file into memory.  <a href="classtensorNet.html#a89755f8e4b72ead7460deed394967386">More...</a><br /></td></tr>
<tr class="separator:a89755f8e4b72ead7460deed394967386 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">EnableLayerProfiler</a> ()</td></tr>
<tr class="memdesc:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable layer profiling times.  <a href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">More...</a><br /></td></tr>
<tr class="separator:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">EnableDebug</a> ()</td></tr>
<tr class="memdesc:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable debug messages and synchronization.  <a href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">More...</a><br /></td></tr>
<tr class="separator:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">AllowGPUFallback</a> () const</td></tr>
<tr class="memdesc:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if GPU fallback is enabled.  <a href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">More...</a><br /></td></tr>
<tr class="separator:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">GetDevice</a> () const</td></tr>
<tr class="memdesc:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the device being used for execution.  <a href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">More...</a><br /></td></tr>
<tr class="separator:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">GetPrecision</a> () const</td></tr>
<tr class="memdesc:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the type of precision being used.  <a href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">More...</a><br /></td></tr>
<tr class="separator:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">IsPrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type) const</td></tr>
<tr class="memdesc:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check if a particular precision is being used.  <a href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">More...</a><br /></td></tr>
<tr class="separator:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">GetStream</a> () const</td></tr>
<tr class="memdesc:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the stream that the device is operating on.  <a href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">More...</a><br /></td></tr>
<tr class="separator:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">CreateStream</a> (bool nonBlocking=true)</td></tr>
<tr class="memdesc:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and use a new stream for execution.  <a href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">More...</a><br /></td></tr>
<tr class="separator:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">SetStream</a> (cudaStream_t stream)</td></tr>
<tr class="memdesc:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the stream that the device is operating on.  <a href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">More...</a><br /></td></tr>
<tr class="separator:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">GetPrototxtPath</a> () const</td></tr>
<tr class="memdesc:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network prototxt file.  <a href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">More...</a><br /></td></tr>
<tr class="separator:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a> () const</td></tr>
<tr class="memdesc:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the full path to model file, including the filename.  <a href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">More...</a><br /></td></tr>
<tr class="separator:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a03252bed041613fc1afb9d3cbb99663d inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a03252bed041613fc1afb9d3cbb99663d">GetModelFilename</a> () const</td></tr>
<tr class="memdesc:a03252bed041613fc1afb9d3cbb99663d inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the filename of the file, excluding the directory.  <a href="classtensorNet.html#a03252bed041613fc1afb9d3cbb99663d">More...</a><br /></td></tr>
<tr class="separator:a03252bed041613fc1afb9d3cbb99663d inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">GetModelType</a> () const</td></tr>
<tr class="memdesc:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the format of the network model.  <a href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">More...</a><br /></td></tr>
<tr class="separator:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">IsModelType</a> (<a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type) const</td></tr>
<tr class="memdesc:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if the model is of the specified format.  <a href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">More...</a><br /></td></tr>
<tr class="separator:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac583b8de1dd64b47338b4a3eb42ac166 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac583b8de1dd64b47338b4a3eb42ac166">GetInputLayers</a> () const</td></tr>
<tr class="memdesc:ac583b8de1dd64b47338b4a3eb42ac166 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of input layers to the network.  <a href="classtensorNet.html#ac583b8de1dd64b47338b4a3eb42ac166">More...</a><br /></td></tr>
<tr class="separator:ac583b8de1dd64b47338b4a3eb42ac166 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2dcc770a7215e2e76a8d520a36689e16 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2dcc770a7215e2e76a8d520a36689e16">GetOutputLayers</a> () const</td></tr>
<tr class="memdesc:a2dcc770a7215e2e76a8d520a36689e16 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of output layers to the network.  <a href="classtensorNet.html#a2dcc770a7215e2e76a8d520a36689e16">More...</a><br /></td></tr>
<tr class="separator:a2dcc770a7215e2e76a8d520a36689e16 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adcfe61596f291e75a87d36c3771f25df inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#adcfe61596f291e75a87d36c3771f25df">GetInputDims</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:adcfe61596f291e75a87d36c3771f25df inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the dimensions of network input layer.  <a href="classtensorNet.html#adcfe61596f291e75a87d36c3771f25df">More...</a><br /></td></tr>
<tr class="separator:adcfe61596f291e75a87d36c3771f25df inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2d75ef6f579d1a71ff472bfafd0b7795 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2d75ef6f579d1a71ff472bfafd0b7795">GetInputWidth</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a2d75ef6f579d1a71ff472bfafd0b7795 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the width of network input layer.  <a href="classtensorNet.html#a2d75ef6f579d1a71ff472bfafd0b7795">More...</a><br /></td></tr>
<tr class="separator:a2d75ef6f579d1a71ff472bfafd0b7795 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a214a92c41dcdcb58b3cd8496aac0857a inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a214a92c41dcdcb58b3cd8496aac0857a">GetInputHeight</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a214a92c41dcdcb58b3cd8496aac0857a inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the height of network input layer.  <a href="classtensorNet.html#a214a92c41dcdcb58b3cd8496aac0857a">More...</a><br /></td></tr>
<tr class="separator:a214a92c41dcdcb58b3cd8496aac0857a inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2c80d46f8a01335e77e41023544102c9 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2c80d46f8a01335e77e41023544102c9">GetInputSize</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a2c80d46f8a01335e77e41023544102c9 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the size (in bytes) of network input layer.  <a href="classtensorNet.html#a2c80d46f8a01335e77e41023544102c9">More...</a><br /></td></tr>
<tr class="separator:a2c80d46f8a01335e77e41023544102c9 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3a8851513971d11746231d217f57b69f inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3a8851513971d11746231d217f57b69f">GetInputPtr</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a3a8851513971d11746231d217f57b69f inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the CUDA pointer to the input layer's memory.  <a href="classtensorNet.html#a3a8851513971d11746231d217f57b69f">More...</a><br /></td></tr>
<tr class="separator:a3a8851513971d11746231d217f57b69f inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a77703f2a7b59f836c93ae28811e22cb0 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a77703f2a7b59f836c93ae28811e22cb0">GetOutputDims</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a77703f2a7b59f836c93ae28811e22cb0 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the dimensions of network output layer.  <a href="classtensorNet.html#a77703f2a7b59f836c93ae28811e22cb0">More...</a><br /></td></tr>
<tr class="separator:a77703f2a7b59f836c93ae28811e22cb0 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a09d63a8fd906c99f8158bf9460a83c02 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a09d63a8fd906c99f8158bf9460a83c02">GetOutputWidth</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a09d63a8fd906c99f8158bf9460a83c02 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the width of network output layer.  <a href="classtensorNet.html#a09d63a8fd906c99f8158bf9460a83c02">More...</a><br /></td></tr>
<tr class="separator:a09d63a8fd906c99f8158bf9460a83c02 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a613679e8ee5315f3b5b16a39011ba76e inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a613679e8ee5315f3b5b16a39011ba76e">GetOutputHeight</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a613679e8ee5315f3b5b16a39011ba76e inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the height of network output layer.  <a href="classtensorNet.html#a613679e8ee5315f3b5b16a39011ba76e">More...</a><br /></td></tr>
<tr class="separator:a613679e8ee5315f3b5b16a39011ba76e inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae1486438dcdbe0d7f5e88e5336a42efa inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae1486438dcdbe0d7f5e88e5336a42efa">GetOutputSize</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:ae1486438dcdbe0d7f5e88e5336a42efa inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the size (in bytes) of network output layer.  <a href="classtensorNet.html#ae1486438dcdbe0d7f5e88e5336a42efa">More...</a><br /></td></tr>
<tr class="separator:ae1486438dcdbe0d7f5e88e5336a42efa inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e5a4207d90828c31255846b11a431ea inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e5a4207d90828c31255846b11a431ea">GetOutputPtr</a> (uint32_t layer=0) const</td></tr>
<tr class="memdesc:a2e5a4207d90828c31255846b11a431ea inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the CUDA pointer to the output memory.  <a href="classtensorNet.html#a2e5a4207d90828c31255846b11a431ea">More...</a><br /></td></tr>
<tr class="separator:a2e5a4207d90828c31255846b11a431ea inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9dd2db089176ae6878e9ea7dd8fd80c3 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">GetNetworkFPS</a> ()</td></tr>
<tr class="memdesc:a9dd2db089176ae6878e9ea7dd8fd80c3 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network frames per second (FPS).  <a href="classtensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">More...</a><br /></td></tr>
<tr class="separator:a9dd2db089176ae6878e9ea7dd8fd80c3 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a> ()</td></tr>
<tr class="memdesc:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network runtime (in milliseconds).  <a href="classtensorNet.html#a49faef5920860345e503023b7c84423c">More...</a><br /></td></tr>
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<tr class="memitem:ade7badd98d5790b5a58863d56e61e041 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ade7badd98d5790b5a58863d56e61e041">GetNetworkName</a> () const</td></tr>
<tr class="memdesc:ade7badd98d5790b5a58863d56e61e041 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network name (it's filename).  <a href="classtensorNet.html#ade7badd98d5790b5a58863d56e61e041">More...</a><br /></td></tr>
<tr class="separator:ade7badd98d5790b5a58863d56e61e041 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float2&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">More...</a><br /></td></tr>
<tr class="separator:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query, <a class="el" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a> device)</td></tr>
<tr class="memdesc:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">More...</a><br /></td></tr>
<tr class="separator:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">PrintProfilerTimes</a> ()</td></tr>
<tr class="memdesc:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Print the profiler times (in millseconds).  <a href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">More...</a><br /></td></tr>
<tr class="separator:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a981fd607b193866dd90a3e824539a961"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classactionNet.html">actionNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a981fd607b193866dd90a3e824539a961">Create</a> (const char *network=&quot;resnet-18&quot;, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:a981fd607b193866dd90a3e824539a961"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a pre-trained model, either "resnet-18" or "resnet-34".  <a href="classactionNet.html#a981fd607b193866dd90a3e824539a961">More...</a><br /></td></tr>
<tr class="separator:a981fd607b193866dd90a3e824539a961"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6cb72e2b12fe3daf0d0f84c4508939fa"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classactionNet.html">actionNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a6cb72e2b12fe3daf0d0f84c4508939fa">Create</a> (const char *model_path, const char *class_labels, const char *input=<a class="el" href="group__actionNet.html#gaa414276f3672cd7092f4cb6ba2c60a4a">ACTIONNET_DEFAULT_INPUT</a>, const char *output=<a class="el" href="group__actionNet.html#ga98ce3a39afbda984f4d161e907b72b68">ACTIONNET_DEFAULT_OUTPUT</a>, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:a6cb72e2b12fe3daf0d0f84c4508939fa"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="classactionNet.html#a6cb72e2b12fe3daf0d0f84c4508939fa">More...</a><br /></td></tr>
<tr class="separator:a6cb72e2b12fe3daf0d0f84c4508939fa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27b624bc152e626bf91a250d06f077b5"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classactionNet.html">actionNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a27b624bc152e626bf91a250d06f077b5">Create</a> (int argc, char **argv)</td></tr>
<tr class="memdesc:a27b624bc152e626bf91a250d06f077b5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance by parsing the command line.  <a href="classactionNet.html#a27b624bc152e626bf91a250d06f077b5">More...</a><br /></td></tr>
<tr class="separator:a27b624bc152e626bf91a250d06f077b5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a40fe45fb6b886aef7317cfa59f37bced"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classactionNet.html">actionNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a40fe45fb6b886aef7317cfa59f37bced">Create</a> (const <a class="el" href="classcommandLine.html">commandLine</a> &amp;cmdLine)</td></tr>
<tr class="memdesc:a40fe45fb6b886aef7317cfa59f37bced"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance by parsing the command line.  <a href="classactionNet.html#a40fe45fb6b886aef7317cfa59f37bced">More...</a><br /></td></tr>
<tr class="separator:a40fe45fb6b886aef7317cfa59f37bced"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4e70dfc16132513fdec7894224ae71e5"><td class="memItemLeft" align="right" valign="top">static const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a4e70dfc16132513fdec7894224ae71e5">Usage</a> ()</td></tr>
<tr class="memdesc:a4e70dfc16132513fdec7894224ae71e5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Usage string for command line arguments to <a class="el" href="classactionNet.html#a981fd607b193866dd90a3e824539a961" title="Load a pre-trained model, either &quot;resnet-18&quot; or &quot;resnet-34&quot;.">Create()</a>  <a href="classactionNet.html#a4e70dfc16132513fdec7894224ae71e5">More...</a><br /></td></tr>
<tr class="separator:a4e70dfc16132513fdec7894224ae71e5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_static_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Static Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:a57cacfea82e9329c2cf776837dd00aef inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a57cacfea82e9329c2cf776837dd00aef">LoadClassLabels</a> (const char *filename, std::vector&lt; std::string &gt; &amp;descriptions, int expectedClasses=-1)</td></tr>
<tr class="memdesc:a57cacfea82e9329c2cf776837dd00aef inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class descriptions from a label file.  <a href="classtensorNet.html#a57cacfea82e9329c2cf776837dd00aef">More...</a><br /></td></tr>
<tr class="separator:a57cacfea82e9329c2cf776837dd00aef inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa92022958d3a46655a5e2f2ed416e6b5 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa92022958d3a46655a5e2f2ed416e6b5">LoadClassLabels</a> (const char *filename, std::vector&lt; std::string &gt; &amp;descriptions, std::vector&lt; std::string &gt; &amp;synsets, int expectedClasses=-1)</td></tr>
<tr class="memdesc:aa92022958d3a46655a5e2f2ed416e6b5 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class descriptions and synset strings from a label file.  <a href="classtensorNet.html#aa92022958d3a46655a5e2f2ed416e6b5">More...</a><br /></td></tr>
<tr class="separator:aa92022958d3a46655a5e2f2ed416e6b5 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7b87410f9133aea37b46979d543219b9 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7b87410f9133aea37b46979d543219b9">LoadClassColors</a> (const char *filename, float4 *colors, int expectedClasses, float defaultAlpha=255.0f)</td></tr>
<tr class="memdesc:a7b87410f9133aea37b46979d543219b9 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class colors from a text file.  <a href="classtensorNet.html#a7b87410f9133aea37b46979d543219b9">More...</a><br /></td></tr>
<tr class="separator:a7b87410f9133aea37b46979d543219b9 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae5dd58e2481f6c703abb9abbcfce805e inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae5dd58e2481f6c703abb9abbcfce805e">LoadClassColors</a> (const char *filename, float4 **colors, int expectedClasses, float defaultAlpha=255.0f)</td></tr>
<tr class="memdesc:ae5dd58e2481f6c703abb9abbcfce805e inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class colors from a text file.  <a href="classtensorNet.html#ae5dd58e2481f6c703abb9abbcfce805e">More...</a><br /></td></tr>
<tr class="separator:ae5dd58e2481f6c703abb9abbcfce805e inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4fe18908c74efda1708029ca3b04f0e8 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static float4&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a4fe18908c74efda1708029ca3b04f0e8">GenerateColor</a> (uint32_t <a class="el" href="cudaPointCloud_8h.html#ad9bd89745d72dbc52651f62814eed36d">classID</a>, float <a class="el" href="cudaVector_8h.html#ac0d98a665e25ffa6d701a2ce2f6efd12">alpha</a>=255.0f)</td></tr>
<tr class="memdesc:a4fe18908c74efda1708029ca3b04f0e8 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Procedurally generate a color for a given class index with the specified alpha value.  <a href="classtensorNet.html#a4fe18908c74efda1708029ca3b04f0e8">More...</a><br /></td></tr>
<tr class="separator:a4fe18908c74efda1708029ca3b04f0e8 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3c0509631176be6f9e25673cb0aa12dc inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3c0509631176be6f9e25673cb0aa12dc">SelectPrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowInt8=true)</td></tr>
<tr class="memdesc:a3c0509631176be6f9e25673cb0aa12dc inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Resolve a desired precision to a specific one that's available.  <a href="classtensorNet.html#a3c0509631176be6f9e25673cb0aa12dc">More...</a><br /></td></tr>
<tr class="separator:a3c0509631176be6f9e25673cb0aa12dc inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">FindFastestPrecision</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowInt8=true)</td></tr>
<tr class="memdesc:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the fastest native precision on a device.  <a href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">More...</a><br /></td></tr>
<tr class="separator:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">DetectNativePrecisions</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect the precisions supported natively on a device.  <a href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">More...</a><br /></td></tr>
<tr class="separator:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a> (const std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt; &amp;nativeTypes, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type)</td></tr>
<tr class="memdesc:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">More...</a><br /></td></tr>
<tr class="separator:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">DetectNativePrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">More...</a><br /></td></tr>
<tr class="separator:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr class="memitem:a423008d3f4bda6f6a4da403ed76ab0b1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a423008d3f4bda6f6a4da403ed76ab0b1">actionNet</a> ()</td></tr>
<tr class="separator:a423008d3f4bda6f6a4da403ed76ab0b1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab7938cba42b5a647fa939cef3813b80b"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#ab7938cba42b5a647fa939cef3813b80b">init</a> (const char *model_path, const char *class_path, const char *input, const char *output, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback)</td></tr>
<tr class="separator:ab7938cba42b5a647fa939cef3813b80b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aee90270cb01137ac90e0ead3f3678a90"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#aee90270cb01137ac90e0ead3f3678a90">preProcess</a> (void *image, uint32_t width, uint32_t height, <a class="el" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format)</td></tr>
<tr class="separator:aee90270cb01137ac90e0ead3f3678a90"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Protected Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet</a> ()</td></tr>
<tr class="memdesc:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">More...</a><br /></td></tr>
<tr class="separator:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e8dd909e797dfcfbb058dc6b351c586 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e8dd909e797dfcfbb058dc6b351c586">ProcessNetwork</a> (bool sync=true)</td></tr>
<tr class="memdesc:a2e8dd909e797dfcfbb058dc6b351c586 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Execute processing of the network.  <a href="classtensorNet.html#a2e8dd909e797dfcfbb058dc6b351c586">More...</a><br /></td></tr>
<tr class="separator:a2e8dd909e797dfcfbb058dc6b351c586 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2fbc013f70b52f885867302446e0dca1 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2fbc013f70b52f885867302446e0dca1">ProfileModel</a> (const std::string &amp;deployFile, const std::string &amp;modelFile, const std::vector&lt; std::string &gt; &amp;inputs, const std::vector&lt; <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &gt; &amp;inputDims, const std::vector&lt; std::string &gt; &amp;outputs, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, char **engineStream, size_t *engineSize)</td></tr>
<tr class="memdesc:a2fbc013f70b52f885867302446e0dca1 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and output an optimized network model.  <a href="classtensorNet.html#a2fbc013f70b52f885867302446e0dca1">More...</a><br /></td></tr>
<tr class="separator:a2fbc013f70b52f885867302446e0dca1 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7a898dfb2553869cdc318ecb03e153f1 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7a898dfb2553869cdc318ecb03e153f1">ConfigureBuilder</a> (nvinfer1::IBuilder *builder, uint32_t maxBatchSize, uint32_t workspaceSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator)</td></tr>
<tr class="memdesc:a7a898dfb2553869cdc318ecb03e153f1 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Configure builder options.  <a href="classtensorNet.html#a7a898dfb2553869cdc318ecb03e153f1">More...</a><br /></td></tr>
<tr class="separator:a7a898dfb2553869cdc318ecb03e153f1 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6e2fe0a467929d76b20940771b8f96c3 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6e2fe0a467929d76b20940771b8f96c3">ValidateEngine</a> (const char *model_path, const char *cache_path, const char *checksum_path)</td></tr>
<tr class="memdesc:a6e2fe0a467929d76b20940771b8f96c3 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Validate that the model already has a built TensorRT engine that exists and doesn't need updating.  <a href="classtensorNet.html#a6e2fe0a467929d76b20940771b8f96c3">More...</a><br /></td></tr>
<tr class="separator:a6e2fe0a467929d76b20940771b8f96c3 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">PROFILER_BEGIN</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Begin a profiling query, before network is run.  <a href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">More...</a><br /></td></tr>
<tr class="separator:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">PROFILER_END</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">End a profiling query, after the network is run.  <a href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">More...</a><br /></td></tr>
<tr class="separator:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Query the CUDA part of a profiler query.  <a href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">More...</a><br /></td></tr>
<tr class="separator:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected Attributes</h2></td></tr>
<tr class="memitem:a35c03812e2928fb8b551de9a96ddc243"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a35c03812e2928fb8b551de9a96ddc243">mInputBuffers</a> [2]</td></tr>
<tr class="separator:a35c03812e2928fb8b551de9a96ddc243"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5174b850866bd1eaf78265c63fc2a9fe"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a5174b850866bd1eaf78265c63fc2a9fe">mNumClasses</a></td></tr>
<tr class="separator:a5174b850866bd1eaf78265c63fc2a9fe"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a122332ccd3dc605278035fcbde9904a2"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a122332ccd3dc605278035fcbde9904a2">mNumFrames</a></td></tr>
<tr class="separator:a122332ccd3dc605278035fcbde9904a2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9d77f144aae3421c668473456326be2e"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a9d77f144aae3421c668473456326be2e">mSkipFrames</a></td></tr>
<tr class="separator:a9d77f144aae3421c668473456326be2e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab613fe5ebe9cb20de9a09acee631bb96"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#ab613fe5ebe9cb20de9a09acee631bb96">mFramesSkipped</a></td></tr>
<tr class="separator:ab613fe5ebe9cb20de9a09acee631bb96"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a023316e6c0b31d1ccaa8d1a22c8df88b"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a023316e6c0b31d1ccaa8d1a22c8df88b">mCurrentInputBuffer</a></td></tr>
<tr class="separator:a023316e6c0b31d1ccaa8d1a22c8df88b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b671ec5d2faa557f000692b9447ae0b"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a6b671ec5d2faa557f000692b9447ae0b">mCurrentFrameIndex</a></td></tr>
<tr class="separator:a6b671ec5d2faa557f000692b9447ae0b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a90efcce12c5ff5dccfbcd45dbd262cdd"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">mThreshold</a></td></tr>
<tr class="separator:a90efcce12c5ff5dccfbcd45dbd262cdd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae44f92239ad5e5bb4be17c7d9b6ad29e"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classactionNet.html#ae44f92239ad5e5bb4be17c7d9b6ad29e">mLastConfidence</a></td></tr>
<tr class="separator:ae44f92239ad5e5bb4be17c7d9b6ad29e"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Action/activity classification on a sequence of images or video, using TensorRT. </p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a90871793d4922b61bc7ac81d7355d685"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a90871793d4922b61bc7ac81d7355d685">&#9670;&nbsp;</a></span>~actionNet()</h2>

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<p>Destroy. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a423008d3f4bda6f6a4da403ed76ab0b1">&#9670;&nbsp;</a></span>actionNet()</h2>

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<h2 class="groupheader">Member Function Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a4338f944254f92fe33572ea1cc7a9736">&#9670;&nbsp;</a></span>Classify() <span class="overload">[1/2]</span></h2>

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template&lt;typename T &gt; </div>
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<p>Append an image to the sequence and classify the action, returning the index of the top class. </p>
<p>Either the class with the maximum confidence will be returned, or -1 if no class meets the threshold set by <a class="el" href="classactionNet.html#a9628498f941ed6709c6b2e13bbb79e29" title="Set the confidence threshold used for classification.">SetThreshold()</a> or the <code>--threshold</code> command-line argument.</p>
<p>If this frame was skipped due to <a class="el" href="classactionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49" title="Set the number of frames that are skipped in between classifications.">SetSkipFrames()</a> being used, then the last frame's results will be returned. By default, every other frame is skipped in order to lengthen the action's window.</p>
<dl class="params"><dt>Parameters</dt><dd>
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    <tr><td class="paramname">width</td><td>width of the input image in pixels. </td></tr>
    <tr><td class="paramname">height</td><td>height of the input image in pixels. </td></tr>
    <tr><td class="paramname">confidence</td><td>optional pointer to float filled with confidence value. </td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Index of the maximum likelihood class, or -1 on error. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a4c7b95bad0cfa696339590020bc4d7c9">&#9670;&nbsp;</a></span>Classify() <span class="overload">[2/2]</span></h2>

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          <td class="memname">int actionNet::Classify </td>
          <td>(</td>
          <td class="paramtype">void *&#160;</td>
          <td class="paramname"><em>image</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
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        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a>&#160;</td>
          <td class="paramname"><em>format</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>confidence</em> = <code>NULL</code>&#160;</td>
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        <tr>
          <td></td>
          <td>)</td>
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<p>Append an image to the sequence and classify the action, returning the index of the top class. </p>
<p>Either the class with the maximum confidence will be returned, or -1 if no class meets the threshold set by <a class="el" href="classactionNet.html#a9628498f941ed6709c6b2e13bbb79e29" title="Set the confidence threshold used for classification.">SetThreshold()</a> or the <code>--threshold</code> command-line argument.</p>
<p>If this frame was skipped due to <a class="el" href="classactionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49" title="Set the number of frames that are skipped in between classifications.">SetSkipFrames()</a> being used, then the last frame's results will be returned. By default, every other frame is skipped in order to lengthen the action's window.</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">image</td><td>input image in CUDA device memory. </td></tr>
    <tr><td class="paramname">width</td><td>width of the input image in pixels. </td></tr>
    <tr><td class="paramname">height</td><td>height of the input image in pixels. </td></tr>
    <tr><td class="paramname">confidence</td><td>optional pointer to float filled with confidence value. </td></tr>
  </table>
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</dl>
<dl class="section return"><dt>Returns</dt><dd>Index of the maximum likelihood class, or -1 on error. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a6cb72e2b12fe3daf0d0f84c4508939fa">&#9670;&nbsp;</a></span>Create() <span class="overload">[1/4]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_path</em>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_labels</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em> = <code><a class="el" href="group__actionNet.html#gaa414276f3672cd7092f4cb6ba2c60a4a">ACTIONNET_DEFAULT_INPUT</a></code>, </td>
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          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output</em> = <code><a class="el" href="group__actionNet.html#ga98ce3a39afbda984f4d161e907b72b68">ACTIONNET_DEFAULT_OUTPUT</a></code>, </td>
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          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
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          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>&#160;</td>
        </tr>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt_path</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model_path</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">mean_binary</td><td>File path to the mean value binary proto (can be NULL) </td></tr>
    <tr><td class="paramname">class_labels</td><td>File path to list of class name labels </td></tr>
    <tr><td class="paramname">input</td><td>Name of the input layer blob. </td></tr>
    <tr><td class="paramname">output</td><td>Name of the output layer blob. </td></tr>
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will support and be optimized for. </td></tr>
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  </dd>
</dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a981fd607b193866dd90a3e824539a961">&#9670;&nbsp;</a></span>Create() <span class="overload">[2/4]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>network</em> = <code>&quot;resnet-18&quot;</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
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          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
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<p>Load a pre-trained model, either "resnet-18" or "resnet-34". </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a40fe45fb6b886aef7317cfa59f37bced">&#9670;&nbsp;</a></span>Create() <span class="overload">[3/4]</span></h2>

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          <td>(</td>
          <td class="paramtype">const <a class="el" href="classcommandLine.html">commandLine</a> &amp;&#160;</td>
          <td class="paramname"><em>cmdLine</em></td><td>)</td>
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<p>Load a new network instance by parsing the command line. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a27b624bc152e626bf91a250d06f077b5">&#9670;&nbsp;</a></span>Create() <span class="overload">[4/4]</span></h2>

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          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>argc</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">char **&#160;</td>
          <td class="paramname"><em>argv</em>&#160;</td>
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          <td></td>
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<p>Load a new network instance by parsing the command line. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#adcfadd35f1c5bf00e4556d4bb15b7ae4">&#9670;&nbsp;</a></span>GetClassDesc()</h2>

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          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>index</em></td><td>)</td>
          <td> const</td>
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<p>Retrieve the description of a particular class. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#abe3946ca2ec6528cde8af9dd90d986ff">&#9670;&nbsp;</a></span>GetClassLabel()</h2>

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          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>index</em></td><td>)</td>
          <td> const</td>
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<p>Retrieve the description of a particular class. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ab1fa2e71897572a2e894cace9078ec36">&#9670;&nbsp;</a></span>GetClassPath()</h2>

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          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve the path to the file containing the class descriptions. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#afde433b5b807ef910787f1d999cef79a">&#9670;&nbsp;</a></span>GetNumClasses()</h2>

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          <td> const</td>
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<p>Retrieve the number of image recognition classes. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a6516543d67148a4a31efd156579676d4">&#9670;&nbsp;</a></span>GetSkipFrames()</h2>

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<p>Return the number of frames that are skipped in between classifications. </p>
<dl class="section see"><dt>See also</dt><dd>SetFrameSkip for more info. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a8ba975e3e175e751c10e2121d339a4d0">&#9670;&nbsp;</a></span>GetThreshold()</h2>

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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Return the confidence threshold used for classification. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ab7938cba42b5a647fa939cef3813b80b">&#9670;&nbsp;</a></span>init()</h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_path</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em>&#160;</td>
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          <td></td>
          <td>)</td>
          <td></td><td></td>
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<h2 class="memtitle"><span class="permalink"><a href="#aee90270cb01137ac90e0ead3f3678a90">&#9670;&nbsp;</a></span>preProcess()</h2>

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          <td class="paramname"><em>image</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a>&#160;</td>
          <td class="paramname"><em>format</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
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<h2 class="memtitle"><span class="permalink"><a href="#a0d1b5c7a23698972dc4d1646e2a23d49">&#9670;&nbsp;</a></span>SetSkipFrames()</h2>

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          <td class="memname">void actionNet::SetSkipFrames </td>
          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>frames</em></td><td>)</td>
          <td></td>
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<p>Set the number of frames that are skipped in between classifications. </p>
<p>Since <a class="el" href="classactionNet.html" title="Action/activity classification on a sequence of images or video, using TensorRT.">actionNet</a> operates on video sequences, it's often helpful to skip frames to lengthen the window of time the model gets to 'see' an action being performed.</p>
<p>The default setting is 1, where every other frame is skipped. Setting this to 0 will disable it, and every frame will be processed. When a frame is skipped, the classification results from the last frame are returned. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a9628498f941ed6709c6b2e13bbb79e29">&#9670;&nbsp;</a></span>SetThreshold()</h2>

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          <td class="memname">void actionNet::SetThreshold </td>
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<p>Set the confidence threshold used for classification. </p>
<p>Classes with a confidence below this threshold will be ignored. </p><dl class="section note"><dt>Note</dt><dd>this can also be set using the <code>--threshold=N</code> command-line argument. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a4e70dfc16132513fdec7894224ae71e5">&#9670;&nbsp;</a></span>Usage()</h2>

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<p>Usage string for command line arguments to <a class="el" href="classactionNet.html#a981fd607b193866dd90a3e824539a961" title="Load a pre-trained model, either &quot;resnet-18&quot; or &quot;resnet-34&quot;.">Create()</a> </p>

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<h2 class="groupheader">Member Data Documentation</h2>
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<hr/>The documentation for this class was generated from the following file:<ul>
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